Advances in information systems and networked databases continue to spur rapid growth in digital media, e.g., audio, image and video. This is due, in part, to highly efficient manipulation, reproduction, and access afforded by digital media. Data hiding is the process of encoding extra information in digital data, such as video, images or sounds, by making small modifications to the data. Hiding information in sounds or images may be used to supplement an image or sound with additional information, or verify the integrity of the image or sound. The hidden information itself may be text, audio or image data or hyperlinks. For example, text captions may be used to label faces and buildings in an image. A short audio clip may associate a train whistle with an image of a locomotive. A hyperlink may join an image region to another document or data source.
The embedded data typically remains with the image when it is stored or transmitted. The embedded data may be meant to be extracted by an end user, or hidden to the end user. In the former instance, for example, a consumer may extract the embedded data and use it to satisfy an information need. In the latter instance, the embedded data may be a watermark. Watermarking is a technique used to label digital media by hiding copyright or other information into the underlying data. Unlike encryption, for example, which is used to restrict access to data, watermarking is employed to provide solid proof of authorship. Like data hiding generally, the watermark remains with the media. However, unlike data hiding generally, with watermarking the user cannot access the embedded information (i.e., the watermark).
Data hiding in general, and watermarking in particular, typically must satisfy the following requirements to be useful: they must be inaudible, and they must be robust. Although other criteria may be important (such as statistical inaudibility, the support for multiple data embeddings and self-clocking), the inaudibility and the robustness of the resulting data are most important. The first requirement is that the hidden data remain inaudible in the case where the host data is sound data. Otherwise, the quality of the sound may degrade.
The second requirement, robustness, relates to the survivability of the hidden data in light of the manipulation of the media in which it is embedded. Typically, sound data are subject to signal processing operations such as filtering, resampling, compression, noise, cropping, audio-to-digital and subsequent digital-to-audio conversion, etc. Because the host data will invariably be subject to such manipulation, the embedded data must be robust. That is, the embedded data must able to survive after the host data has been subjected to signal processing operations.
Several data hiding techniques are found in the prior art. Some hiding schemes employ spread spectrum techniques. This is typically applied to audio signals. In direct sequence spread spectrum coding, the signature is modulated by both a PN-sequence and the audio signal using bi-phase shift keying. It is then added to the original signal as an additive random noise. However, these schemes fail to meet optimally at least one of the above-identified requirements.
Thus, there is a need for a data hiding and watermarking technique that is inaudible in the case of audio data and has the maximum robustness to ensure that the embedded data survives both legitimate and illegitimate data manipulation.